Machine Learning Platform Engineer - Cloud Services

Title - ML Platform Engineer Salary : 18-24 LPA Location : Pan India Mode : Remote Required skills : - 10 years of professional experience in building applications using cloud services. - Prior experience in building Machine Learning platforms using cloud services. - Cloud expertise : Deep knowledge of cloud platforms like AWS, Google Cloud Platform, or Azure, including their machine learning and data services (Azure preferred). - DevOps skills : Experience with CI/CD pipelines, infrastructure as code, and containerization technologies like Docker and Kubernetes. - Machine learning knowledge : Understanding of ML workflows, model training, and deployment processes. - Data engineering : Familiarity with data pipelines, ETL processes, and data storage solutions. - Software engineering : Strong programming skills, particularly in languages commonly used in ML like Python. - System design : Ability to architect scalable, reliable systems that integrate various services. - Automation : Expertise in automating workflows and processes across the ML lifecycle. - Security and compliance : Knowledge of best practices for securing ML pipelines and ensuring regulatory compliance. - Monitoring and logging : Experience setting up monitoring and logging for ML systems. - Collaboration : Ability to work with data scientists, software engineers, and other stakeholders. Roles & responsibilities : - Evaluate and select appropriate cloud services for each stage of the ML lifecycle Design and implement the overall architecture of the MLOps platform - Set up automated pipelines for data preparation, model training, and deployment Implement version control for code, data, and models - Ensure the platform is scalable, secure, and compliant with relevant regulations - Provide tools and interfaces for data scientists to easily leverage the platform - Continuously optimize the platform for performance and cost-efficiency This role is crucial in bridging the gap between data science and operations, enabling organizations to efficiently develop, deploy, and maintain machine learning models at scale. (ref:hirist.tech)

Location: in, IN

Posted Date: 1/15/2025